Using EHR Information to Estimate Mortality Risk for People With Dementia in an Australian Nursing Home Setting

End-of-life care for people with dementia is mainly delivered in nursing homes, but prognostic uncertainty often hinders timely access to specialist palliative care and anticipatory planning. Existing electronic health record (EHR) systems in Australian nursing homes do not adequately support the identification of residents at risk of deterioration. This study explored nursing home EHR data in Australia to identify factors associated with mortality risk among residents with dementia.

Secondary analysis of the IMPETUS-D study, a cluster randomized trial of a palliative care education intervention for nursing home staff.

People with dementia from 24 nursing homes in Australia with moderate to severe cognitive impairment (aged care funding instrument cognitive skills C or D).

Baseline data were collected between October 2018 and September 2019, with follow-up mortality data until September 30, 2020. Candidate predictor variables (CPVs) were identified from EHR information, selected based on a literature review of factors associated with increased mortality, and limited to 10 variables to ensure a minimum of 20 events per CPV. A Cox proportional hazards model for the relationship between variables and mortality was developed using backward elimination at a P value threshold of >0.10.

Of 922 people with dementia, 296 deaths occurred during follow-up. Five CPVs were retained in the final model: age, male sex, level of assistance required for oral intake, baseline weight, and change in weight over 6 months. The model showed moderate mortality discrimination (apparent c-statistic, 0.64; optimism-corrected c-statistic, 0.61) and acceptable calibration (optimism-corrected calibration slope, 0.82).

A model using routinely collected EHR data identified key predictors of mortality among nursing home residents with dementia in Australia. With further validation, these predictors could leverage nursing home EHR systems to improve anticipatory care planning for people with dementia at increased risk of deterioration.